Prediction of solar Stirling power generation in smart grid by GA-ANN model Online publication date: Wed, 01-Mar-2017
by Mohammad Sameti; Mohammad Ali Jokar; Fatemeh Razi Astaraei
International Journal of Computer Applications in Technology (IJCAT), Vol. 55, No. 2, 2017
Abstract: A model based on the feed-forward Artificial Neural Network (ANN) optimised by the Genetic Algorithm (GA) is developed in order to estimate the power of a solar Stirling heat engine in a smart grid. Genetic Algorithm is used to decide the initial weights of the neural network. The GA-ANN model is applied to predict the power of the solar Stirling heat engine from a data set reported in literature. The performance of the GA-ANN model is compared with numerical data. The results demonstrate the effectiveness of the GA-ANN model.
Online publication date: Wed, 01-Mar-2017
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